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More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. Predictiveanalytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.
To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with bigdata platforms such as Hadoop or Apache Spark. Prescriptiveanalytics: Prescriptiveanalyticspredicts likely outcomes and makes decision recommendations.
While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to bigdata while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.
4) Predictive And PrescriptiveAnalytics Tools. Business analytics of tomorrow is focused on the future and tries to answer the questions: what will happen? There are plenty of bigdata examples used in real life, shaping our world, be it in the buying experience or managing customers’ data.
Predictive & PrescriptiveAnalytics. PredictiveAnalytics: What could happen? We mentioned predictiveanalytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2020. PrescriptiveAnalytics: What should we do?
Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptiveanalytics for business forecasting and optimization, respectively. How do predictive and prescriptiveanalytics fit into this statistical framework?
Ideally, your primary data source should belong in this group. Modern Data Sources Painlessly connect with modern data such as streaming, search, bigdata, NoSQL, cloud, document-based sources. Quickly link all your data from Amazon Redshift, MongoDB, Hadoop, Snowflake, Apache Solr, Elasticsearch, Impala, and more.
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